Tech Lead, Software Engineer, Cloud Engineer - Software

Most tech lead roles ask you to scale systems. This one asks you to redefine how they’re built.

At Advisor
360°, we’re not just building software, we’re building the system that builds the software. This is a rare opportunity to step into a true player‑coach role where your impact goes far beyond code. You’ll architect not only products, but the way humans and AI agents collaborate to create them.

If you’ve ever thought “there has to be a better way to build,” this is your chance to prove it.

You’ll lead a small, autonomous team at the intersection of engineering, AI, and product. You’ll design systems that scale, but more importantly, systems that learn. Every decision you make compounds, shaping how work gets done, how quality is enforced, and how fast great ideas turn into production reality.

This is not about keeping the lights on. It’s about building what comes next.

This role is remote or hybrid, requiring three days per week onsite in our Needham, MA headquarters.

In this role you will own the technical architecture and engineering leadership for a product within an AI-native product line at Advisor
360°, a leading enterprise wealth tech platform. You’ll lead the engineering side of a 5-person autonomous team, taking full ownership of architecture, quality, and technical decision-making. This is a true player‑coach role where you not only design and build critical parts of the system, but more importantly elevate the effectiveness of both your team and AI agents through the systems and patterns you create.

In doing so, you’ll help define what agentic software development looks like in practice and play a key role in shaping a new model for how modern B2B software gets built.

• Own the technical architecture for your team's product surface — service boundaries, data flow, API design, infrastructure decisions, and scaling strategy for large‑scale SaaS
• Review and approve product specifications before build begins — your job is to ensure specs give both humans and AI agents enough technical context to execute well
• Author and maintain the team's agentic ecosystem — CLAUDE.md files, MCP server configurations, custom slash commands, agent hooks, and workflow templates. These artifacts teach AI agents how to work in your codebase and are the single most leveraged system you own
• Build and own the AI‑powered test automation pipeline — consume the Product Lead's user stories and acceptance criteria to drive automated e2e test generation, regression suites, and CI‑integrated quality gates
• Review agent‑generated code for architecture alignment, security, performance, and correctness — agents produce volume, you provide judgment
• Run the compound loop — after each feature ships, encode what worked and what didn't back into the system so agents and engineers get better with every cycle
• Make architecture decisions that hold up at scale — real‑time data processing, cloud‑native infrastructure, API design for high‑throughput environments
• Write code selectively — architecturally novel problems, security‑critical paths, and reference implementations that set the patterns agents follow
• Direct AI agents on well‑scoped implementation tasks while personally handling the work that requires deep system understanding

• 8+ years as a software engineer, with at least 2 years in a tech lead, staff engineer, or architect role at a large‑scale B2B SaaS company
• Deep architecture experience — you've designed and shipped systems involving real‑time data processing, cloud infrastructure, distributed services, and API‑driven platforms
• Strong cloud infrastructure depth — AWS (or equivalent), streaming architectures, large‑scale data processing. You've built systems that handle significant throughput in production
• Hands‑on engineering ability — you can still build, not just draw diagrams. You write code when it matters
• Experience with AI coding tools — you've used Claude Code, Cursor, or similar and have opinions on where agents help vs. where they fail
• Strong system design instincts — can articulate
  * why* an architecture decision is right, not just
  * what* it is
• Experience…